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Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

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Penalized estimation for proportional hazards models with current status data.

Minggen Lu¹, Chin-Shang Li²

¹School of Community Health Sciences, University of Nevada, Reno, NV, U.S.A.

Statistics in Medicine

|September 6, 2017

Summary

This study introduces a penalized estimation method for Cox proportional hazards models with current status data, offering optimal convergence rates and efficient regression parameter estimation. The approach demonstrates strong finite-sample performance in simulations.

Keywords:

current status data efficient estimation goodness-of-fit isotonic regression monotone B-spline penalized estimation

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Area of Science:

Biostatistics
Survival Analysis
Statistical Modeling

Background:

Current status data presents unique challenges in survival analysis.
Existing methods for Cox proportional hazards models may lack flexibility or efficiency with this data type.

Purpose of the Study:

To develop a simple, practical, and flexible penalized estimation method for Cox proportional hazards models using current status data.
To evaluate the theoretical properties and finite-sample performance of the proposed method.

Main Methods:

Approximation of the baseline cumulative hazard function using monotone B-splines.
Hybrid estimation approach combining Fisher-scoring algorithm and isotonic regression.
Asymptotic analysis of regression parameter estimators and development of a variance estimation method.

Main Results:

The penalized estimator achieves optimal convergence rates under smooth conditions.
Regression parameter estimators are asymptotically normal and efficient.
Monte Carlo studies confirm good finite-sample performance compared to existing R packages.

Conclusions:

The proposed penalized estimation method is a viable and effective tool for analyzing current status data within the Cox proportional hazards framework.
The method offers theoretical advantages and practical utility, supported by simulation studies and real-data applications.